1. Field
Embodiments of the present invention relate generally to object-oriented databases (OODBs). More specifically, embodiments relate to memory management methods and systems in such databases.
2. Description of Related Art
In the information age, databases are a precious commodity, storing immense quantities of data for use in various applications. Latency, or time needed to access stored database data, is a crucial metric for many performance-intensive applications. Portfolio management applications, for example, are generally performance-intensive.
In-memory databases are the fastest possible databases. In such databases, which place the dataset in main memory, any piece of information is available with almost zero latency. The memory requirements of such databases increase with the size of the stored dataset. Therefore, such databases become excessively expensive from a hardware perspective when datasets are very large. In addition, computer manufacturers limit the amount of memory that can be installed in their machines, which limits the maximum size of the dataset that can be stored.
Some database systems address this memory problem by using software to cache portions of the dataset in main memory while keeping the majority in secondary memory (i.e., secondary storage), such as on disk. While this approach solves one problem, it creates another: Complex software must keep track of the location of the objects being stored, moving copies of the in-memory objects back and forth from the disk. This approach also increases complexity and latency, as software must determine where to look for the object, i.e., in memory or on disk. In addition, desired data must be copied to the application's memory space because, for data integrity and functional reasons, users cannot be allowed direct access to the database copy of the object, whether it is found in the memory cache or on the disk.
Improvements to address these issues were developed and described in U.S. Pat. No. 7,222,117, for “Segmented Global Area Database,” issued May 22, 2007, by McGrogan, which is incorporated herein in its entirety by this reference. An embodiment of that invention is sometimes referred to herein as “SAGA.”
A need exists to scale up SAGA for larger data volumes.